Multi-channel audio data are typically intended for several respective audio tracks. Several respective sound sources may be used to help to afford the listener the illusion of surround sound.
Multi-channel audio data may for example comprise stereo data on two channels, or else 5.1 data on six channels, in particular for Home Cinema applications. The invention can also find an application in the field of spatialized audio conferences, where the data corresponding to a speaker undergo spatialization processing so as to afford the listener the illusion that this speaker's voice is originating from a particular position in space.
Spatialization data are used to obtain multi-channel data on the basis of the data on a smaller number of channels, for example mono-channel data. These spatialization data can for example comprise differences of inter-pathway level or ILDs (“Interchannel Level Differences”), inter-pathway correlations or ICCs (“Interchannel Cross Correlations”), delays between pathways or ITDs (“Interchannel Time Differences”), phase differences between pathways or IPDs (“Interchannel Phase Differences”), or the like.
It may happen that audio data received, comprising at least the mono-channel data and the spatialization data, are defective, that is to say certain data are missing, or else erroneous.
The detection of this defective transmission may be performed by way of a code of CRC (“Cyclic Redundancy Check”) type.
It is known to alleviate these defects by replacing defective values with predicted values. These predicted values may be determined in accordance with a known prediction model.
Several prediction models are known. For example, one chooses as predicted value an arbitrary value, a previous value, a value determined on the basis of the audio data previously received in accordance with for example methods of linear prediction, or the like.
When mono-channel data are received in a defective manner, the replacing of the defective values with predicted values of mono-channel data turns out in general to be relatively satisfactory.
However, when spatialization data are received in a defective manner, the replacing of the defective values with predicted values may turn out to be unsatisfactory.
Strong variations of the spatialization data over time are manifested for the listener by the sensation of abrupt displacements of the sound sources.
For example, if defective values are replaced with an arbitrary value corresponding to an absence of spatialization, the sensation of returning to a mono-channel sound may be disruptive for the listener, in particular in the case of binaural signals. Indeed, binaural signals, that is to say allowing faithful playback in 3D space at the level of the ears, often correspond to virtual sound sources relatively fixed in space.
There therefore exists a requirement for better concealment of the defects of spatialization data during the reconstruction of multi-channel audio data.